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Abstract Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for continuous monitoring and are relatively easy to implement, these methods have become an important tool for recognizing when, where, and under what conditions PF occurs. The methods seek to identify a pattern or quantification that indicates the occurrence of PF. Most commonly, the chosen signature is either (1) a nonsequential response to infiltrated water, in which soil moisture responses do not occur in order of shallowest to deepest, or (2) a velocity criterion, in which newly infiltrated water is detected at depth earlier than is possible by nonpreferential flow processes. Alternative signatures have also been developed that have certain advantages but are less commonly utilized. Choosing among these possible signatures requires attention to their pertinent characteristics, including susceptibility to errors, possible bias toward false negatives or false positives, reliance on subjective judgments, and possible requirements for additional types of data. We review 77 studies that have applied such methods to highlight important information for readers who want to identify PF from soil moisture data and to inform those who aim to develop new methods or improve existing ones. 

Abstract Reductions in streamflow caused by groundwater pumping, known as “streamflow depletion,” link the hydrologic process of stream‐aquifer interactions to human modifications of the water cycle. Isolating the impacts of groundwater pumping on streamflow is challenging because other climate and human activities concurrently impact streamflow, making it difficult to separate individual drivers of hydrologic change. In addition, there can be lags between when pumping occurs and when streamflow is affected. However, accurate quantification of streamflow depletion is critical to integrated groundwater and surface water management decision making. Here, we highlight research priorities to help advance fundamental hydrologic science and better serve the decision‐making process. Key priorities include (a) linking streamflow depletion to decision‐relevant outcomes such as ecosystem function and water users to align with partner needs; (b) enhancing partner trust and applicability of streamflow depletion methods through benchmarking and coupled model development; and (c) improving links between streamflow depletion quantification and decision‐making processes. Catalyzing research efforts around the common goal of enhancing our streamflow depletion decision‐support capabilities will require disciplinary advances within the water science community and a commitment to transdisciplinary collaboration with diverse water‐connected disciplines, professions, governments, organizations, and communities. 

Effective groundwater management is critical to future environmental, ecological, and social sustainability and requires accurate estimates of groundwater withdrawals. Unfortunately, these estimates are not readily available in most areas due to physical, regulatory, and social challenges. Here, we compare four different approaches for estimating groundwater withdrawals for agricultural irrigation. We apply these methods in a groundwater‐irrigated region in the state of Kansas, USA, where high‐quality groundwater withdrawal data are available for evaluation. The four methods represent a broad spectrum of approaches: (1) the hydrologically‐based Water Table Fluctuation method (WTFM); (2) the demand‐based SALUS crop model; (3) estimates based on satellite‐derived evapotranspiration (ET) data from OpenET; and (4) a landscape hydrology model which integrates hydrologic‐ and demand‐based approaches. The applicability of each approach varies based on data availability, spatial and temporal resolution, and accuracy of predictions. In general, our results indicate that all approaches reasonably estimate groundwater withdrawals in our region, however, the type and amount of data required for accurate estimates and the computational requirements vary among approaches. For example, WTFM requires accurate groundwater levels, specific yield, and recharge data, whereas the SALUS crop model requires adequate information about crop type, land use, and weather. This variability highlights the difficulty in identifying what data, and how much, are necessary for a reasonable groundwater withdrawal estimate, and suggests that data availability should drive the choice of approach. Overall, our findings will help practitioners evaluate the strengths and weaknesses of different approaches and select the appropriate approach for their application. 

Abstract Deep soils represent a dynamic interface between surface soils and saprolite or bedrock, influencing water flow, solute and gas exchange, and mineral and organic matter transformations from local to global scales. Root architecture reflects land cover and soil heterogeneity, enabling vegetation access to resources that vary temporally and spatially while shaping soil structure and formation. However, how land use can influence roots and soil structure relatively deep in the subsurface (>30 cm) remains poorly understood. We investigate how cropland‐related land use and subsequent vegetation recovery alter rooting dynamics and soil structure in deeper horizons. Using a large‐scale data set representing multiple land uses as a means of varying root abundance across four soil orders, we demonstrate that B horizon root loss and regeneration are linked to changes in multiple soil structural attributes deep within soil profiles. Our findings further suggest that the degree of soil development modulates the extent of structural transformations, with less‐developed soils showing greater susceptibility to root‐associated structural shifts. The greatest change in structural development and distinctness was observed in Inceptisols, while Ultisols exhibited the least change. Such soil structural changes affect water flowpaths, carbon retention, and nutrient transport throughout the subsurface. This work thus underscores the need for Earth system models to capture dynamic soil structural attributes that respond to land‐use change. We suggest that changes in deep‐rooting abundance, such as those accelerating in the Anthropocene, may be an important agent of subsurface structural change with meaningful implications for contemporary and future ecosystem feedbacks to climate. 

Abstract Mountain System Recharge processes are significant natural recharge pathways in many arid and semi‐arid mountainous regions. However, Mountain System Recharge processes are often poorly understood and characterized in hydrologic models. Mountains are the primary water supply source to valley aquifers via lateral groundwater flow from the mountain block (Mountain Block Recharge) and focused recharge from mountain streams contributing to focused Mountain Front Recharge at the piedmont zone. Here, we present a multi‐tool isogeochemical approach to characterize mountain flow paths and Mountain System Recharge in the northern Tulare Basin, California. We used groundwater chemistry data to delineate hydrochemical facies and explain the chemical evolution of groundwater from the Sierra Nevada to the Central Valley aquifer. Stable isotopes and radiogenic groundwater tracers validated Mountain System Recharge processes by differentiating focused from diffuse recharge, and estimating apparent groundwater age, respectively. Novel application of End‐Member Mixing Analysis using conservative chemical components revealed three Mountain System Recharge end‐members: (a) evaporated Ca‐HCO₃water type associated with focused Mountain Front Recharge, (b) non‐evaporated Ca‐HCO₃and Na‐HCO₃water types with short residence times associated with shallow Mountain Block Recharge, and (c) Na‐HCO₃groundwater type with long residence time associated with deep Mountain Block Recharge. We quantified the contribution of each Mountain System Recharge process to the valley aquifer by calculating mixing ratios. Our results show that deep Mountain Block Recharge is a significant recharge component, representing 31%–53% of the valley groundwater. Greater hydraulic connectivity between the Sierra Nevada and Central Valley has significant implications for parameterizing groundwater flow models. Our framework is useful for understanding Mountain System Recharge processes in other snow‐dominated mountain watersheds. 

The condition of the Salton Sea, California's largest lake, has profound implications for people and wildlife both near and far. Colorado River irrigation water has supported agricultural productivity in the basin's Coachella and Imperial valleys since the Sea formed over 100 years ago, bringing billions of dollars per year to the region and helping to feed households across the United States. The runoff, which drains into the Sea, has historically maintained water levels and supported critical fish and migratory bird habitats. However, since 2018, a large portion of the water previously allocated for agriculture has been diverted to urban regions, causing the Sea to shrink and become increasingly saline. This poses major threats to the Sea's ecology, as well as risks to human health, most notably in the noxious dust produced by the drying lakebed. To ensure continued agricultural and ecological productivity and protect public health, management of the Sea and surrounding wetlands will require increased research and mitigation efforts. 

Abstract. Mountainous regions act as the water towers of the worldby producing streamflow and groundwater recharge, a function that isparticularly important in semiarid regions. Quantifying rates of mountainsystem recharge is difficult, and hydrologic models offer a method toestimate recharge over large scales. These recharge estimates are prone touncertainty from various sources including model structure and parameters.The quality of meteorological forcing datasets, particularly in mountainousregions, is a large source of uncertainty that is often neglected ingroundwater investigations. In this contribution, we quantify the impact ofuncertainty in both precipitation and air temperature forcing datasets onthe simulated groundwater recharge in the mountainous watershed of theKaweah River in California, USA. We make use of the integrated surface water–groundwater model, ParFlow.CLM, and several gridded datasets commonly usedin hydrologic studies, downscaled NLDAS-2, PRISM, Daymet, Gridmet, andTopoWx. Simulations indicate that, across all forcing datasets, mountain front recharge is an important component of the water budget in themountainous watershed, accounting for 9 %–72 % of the annual precipitation and ∼90 % of the total mountain system recharge to theadjacent Central Valley aquifer. The uncertainty in gridded air temperatureor precipitation datasets, when assessed individually, results in similarranges of uncertainty in the simulated water budget. Variations in simulatedrecharge to changes in precipitation (elasticities) and air temperature(sensitivities) are larger than 1 % change in recharge per 1 % change inprecipitation or 1 ∘C change in temperature. The total volume ofsnowmelt is the primary factor creating the high water budget sensitivity, and snowmelt volume is influenced by both precipitation and air temperatureforcings. The combined effect of uncertainty in air temperature andprecipitation on recharge is additive and results in uncertainty levels roughly equal to the sum of the individual uncertainties depending on thehydroclimatic condition of the watershed. Mountain system recharge pathwaysincluding mountain block recharge, mountain aquifer recharge, and mountainfront recharge are less sensitive to changes in air temperature than changesin precipitation. Mountain front and mountain block recharge are moresensitive to changes in precipitation than other recharge pathways. Themagnitude of uncertainty in the simulated water budget reflects theimportance of developing high-quality meteorological forcing datasets in mountainous regions.